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A Maiden Application of Competitive Swarm Optimizer for Solution of Economic Load Dispatch with Parameter Estimation

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Metaheuristic and Evolutionary Computation: Algorithms and Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 916))

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Abstract

This work, presents a novel application of newly developed Competitive Swarm Optimizer (CSO) in solving a non-linear, non-convex and constrained Economic Load Dispatch (ELD) problem of power systems. A comparative analysis is performed between Particle Swarm Optimization (PSO) and CSO. CSO is basically inspired by the behavior of well-known PSO algorithm. Similar to PSO, CSO is also swarm based optimization technique and has both cognitive as well as social component. The difference lies in the fact that CSO neither uses local best nor global best in updating the position of their particles, which makes the algorithm memory free. A pair wise competition is performed and only loser particles are updated after getting experience from the winner one. The performance of algorithm is tested on 4 benchmark systems with 5 case studies. Case studies include both small as well as bigger system with various degree of constraints such as; Power balance, Prohibited Operating Zone (POZ), ramp limits, valve point loading etc. Moreover, general and standard statistical tests (t-test) are also performed to investigate the consistency and robust of the proposed algorithm. The performance of CSO is significantly dependent on its social factor (ϕ) and population size. In view of this, in the present work the performance of CSO with the variation in population size and (ϕ) are also studied. Parametric study is also performed for all cases to judge the sensitivity of the algorithm. The study reveals that the proper tuning of social factor (ϕ) and population size significantly reduce the search space which helps the algorithm to accelerate its convergence.

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Authors and Affiliations

  1. Electrical and Electronics Engineering Department, NIT Sikkim, Ravangla, India

    Abhishek Rajan

  2. Oil and Natural Gas Corporation, Mumbai, India

    Abhay Sahu

  3. Samsung India R&D, Bengaluru, India

    Debashish Deka

  4. Electrical Engineering Department, NIT Silchar, Silchar, Assam, India

    Tanmoy Malakar

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  1. Abhishek Rajan
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  2. Abhay Sahu
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  3. Debashish Deka
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  4. Tanmoy Malakar
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Correspondence to Abhishek Rajan .

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Editors and Affiliations

  1. ICE Division, NSUT, Delhi, India

    Hasmat Malik

  2. Dept. of Electrical Engineering, Qatar University, Qatar, Qatar

    Atif Iqbal

  3. Electrical Engineering Department, Rajkiya Engineering College, Uttar Pradesh, India

    Puneet Joshi

  4. Electrical Engineering Department, Rajkiya Engineering College, Uttar Pradesh, India

    Sanjay Agrawal

  5. Electrical Engineering Department, National Institute of Technology, Srinagar, India

    Farhad Ilahi Bakhsh

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Conflict of Interest: Abhishek Rajan declares that he has no conflict of interest. Abhay Sahu declares that he has no conflict of interest. Debashish Deka declares that he has no conflict of interest. T. Malakar declares that he has no conflict of interest.

Ethical Approval: This article does not contain any studies with human participants or animals performed by any of the authors.

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Rajan, A., Sahu, A., Deka, D., Malakar, T. (2021). A Maiden Application of Competitive Swarm Optimizer for Solution of Economic Load Dispatch with Parameter Estimation. In: Malik, H., Iqbal, A., Joshi, P., Agrawal, S., Bakhsh, F.I. (eds) Metaheuristic and Evolutionary Computation: Algorithms and Applications. Studies in Computational Intelligence, vol 916. Springer, Singapore. https://doi.org/10.1007/978-981-15-7571-6_14

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